1. Field of the Invention
The present invention relates to discrimination of an object included in image data and more particularly to improvement in the speed of discrimination that uses a plurality of discriminators.
2. Description of the Related Art
Boosting is an algorithm for building an accurate discriminator by combining a plurality of discriminators which are not necessarily accurate. Discriminators learned through the boosting are used in various sectors of industry as described, for example, in Y. Freund and R. E. Schapire, “A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting”, Journal of Computer and System Sciences, vol. 55, pp. 119-139, 1997.
In particular, discriminators are used in face detection, face recognition, and the like, and have become familiar in our life due to wide spread use of digital cameras and video cameras. The face detector is a discriminator that receives a luminance value of a certain image area, as input data, and discriminates whether or not a face is present in the image area. The research of face detection has been conducted from the latter half of 1990s, but a practical method was not developed due to calculation speed. But real time face detection has become possible by a face detector proposed by Viola and Jones. The detector employs a weak classifier that uses a Haar-Like feature (FIG. 20) that allows rapid calculation.
The reason why boosting is used for face detection is that more importance is placed on the discrimination time of actual discrimination than on the time required for learning a discrimination apparatus. One of the reasons why the boosting allows rapid discrimination in the face detection problem is the employment of the feature that allows rapid calculation described above. In addition, the use of a method in which evaluation of weak classifiers is terminated halfway is another point of rapid face detection. The discrimination apparatus which can be obtained by boosting is a liner connection of weak classifiers, and a method in which these classifies are evaluated successively to obtain a final discrimination result is generally used.
Generally, a probability that a face is present in an image is low and many weak classifiers classify as “not a face”. For a discrimination apparatus which includes many weak classifiers that classify as “not a face”, termination of the evaluation halfway may reduce the average time required for the discrimination. In particular, if a weak classifier having a high contribution to classification of “not a face” is evaluated first, the evaluation can be terminated in an earlier stage. That is, the order of arrangement of the weak classifiers is an important factor for rapid discrimination.
Heretofore, the arrangement order of a group of weak classifiers provided by the boosting or the like is designed based on the assumption that all weak classifiers are used. Thus, discrimination only by some of the weak classifiers instead of using all the classifiers will result in sacrifice of accuracy, and it has been difficult to enhance the overall performance in which the discrimination speed and accuracy are balanced.
In view of the circumstances described above, it is an object of the present invention to provide a rapid discrimination apparatus, which includes a plurality of weak classifiers, capable of performing rapid discrimination without sacrificing discrimination accuracy, a method for speeding up the rapid discrimination apparatus, and a program of the rapid discrimination apparatus.